How We Reduced AWS Costs for Our Client by more than 40%

Managing cloud costs is critical for businesses leveraging AWS—or any cloud service—to ensure their operations remain efficient and profitable. With AWS’s vast array of services and flexible pricing models, it’s easy for costs to spiral out of control if not continuously monitored. At Cloud Zappy, we recently undertook a cost-optimization project for one of our clients and achieved more than 40% reduction in their AWS expenses. Here’s how we did it.

Why Should You Continuously Monitor AWS Costs?

AWS provides unparalleled scalability and performance, but it also comes with complexity. Costs can rise unexpectedly due to factors such as unused resources, inefficient configurations, or redundant services. Regular audits and optimizations are necessary to:

• Identify unnecessary expenditures.
• Ensure resources are right-sized for workloads.
• Align expenses with business priorities.

For our client, we noticed their AWS bills were steadily climbing, making it crucial to implement a comprehensive cost-reduction strategy.

Step 1: Leveraging Graviton Processors for Cost Efficiency and Performance

Our first step was to analyze the client’s existing infrastructure. We identified workloads that could benefit from Graviton processors, which are designed by AWS to deliver better price-performance ratios. By migrating these workloads to Graviton2-based instances, we:

• Improved performance for compute-intensive applications.
• Reduced the cost per instance due to Graviton’s energy-efficient architecture.

This shift resulted in immediate savings while maintaining—and in some cases enhancing—application performance.

Step 2: Optimizing RDS with T4g Instances

For their relational database services (RDS), we migrated instances to T4g, which are optimized for burstable performance and lower cost. This allowed the client to:

• Maintain reliable database performance.
• Reduce costs by leveraging the T4g’s lower price point for workloads with variable demands.
• Updated to Maria DB 11.4 and optimized databases through indexes and clean-ups which reduced database load and hence, reduced the need for high capacity instances.

Step 3: Automating Resource Utilization

One of the biggest cost drains was unused development instances and orphaned resources. Here’s how we addressed this:

• Automation: We implemented automated scripts to turn development instances on in the morning and off during non-working hours, ensuring resources were utilized only when needed.
• Cleanup: We removed abandoned instances and deleted unused data, which were previously inflating storage costs.

This step not only reduced costs but also improved resource management.

Step 4: Transitioning to IPv6 to Avoid New Charges

With AWS introducing additional charges for IPv4 addresses starting February 1, 2024, we proactively transitioned the client’s systems to IPv6 where feasible. By releasing unused IPv4 addresses, we:

• Avoided future cost increases.
• Adopted a more future-proof and scalable IP addressing system.

Step 5: Cleaning Up Redundant Resources

We conducted a thorough audit of the client’s AWS environment and identified the following redundancies:

• Unused Route 53 Load Balancers: These were promptly removed.
• Unused VPCs: Unnecessary Virtual Private Clouds were deleted.
• Excess S3 Logs: We deleted outdated logs and implemented a retention policy to ensure logs are only stored when necessary.

Step 6: Optimizing Backup Schedules

Backup schedules were another area of cost inefficiency. The client’s default backup schedules were retaining data for longer than necessary. We optimized this by:

• Reducing the retention period for backups to three days.
• Implementing lifecycle policies to automatically move older backups to cheaper storage tiers or delete them entirely.

Step 7: Right-Sizing Production Instances

We carefully evaluated the client’s production workloads and resized instances at every stage of the pipeline. By selecting appropriately sized instances for each workload, we:

• Reduced underutilized capacity.
• Ensured workloads ran efficiently without overspending on oversized instances.

The Results

By combining these strategies, we achieved more than 40% reduction in AWS costs for our client. Here’s a quick recap of the key changes:

• Migrated workloads to Graviton processors.
• Optimized RDS with T4g instances.
• Automated resource utilization to minimize waste.
• Transitioned to IPv6 to avoid new IPv4 charges.
• Removed redundant resources like unused load balancers and VPCs.
• Optimized backup schedules to reduce storage costs.
• Right-sized production instances.

Conclusion

Reducing AWS costs requires a blend of technical expertise and diligent monitoring. For our client, this meant addressing inefficiencies across compute, storage, and networking resources while ensuring their systems continued to perform seamlessly. If your AWS bills are climbing and you’re unsure how to tackle them, we’re here to help.

Ready to Optimize Your AWS Costs? Contact Cloud Zappy today to learn how we can help your business maximize efficiency while minimizing expenses.